WHAT'S NEW
FACTORS INFLUENCING EARLY CHILDHOOD DEVELOPMENT IN TASMANIA
For the first time, data from the Census of Population and Housing (Census), the Australian Early Development Census (AEDC, formerly the Australian Early Development Index) and National Early Childhood Education and Care Collection (NECECC) has been integrated, to produce a dataset capable of providing new insights on the extent to which preschool participation and parental, family and household characteristics affect children's development. This work follows on from earlier ABS studies utilising Census data combined with AEDC data for Queensland, and National Assessment Program – Literacy and Numeracy (NAPLAN) data for Queensland and Tasmania, such as the study described below.
The AEDC provides some demographic data such as Indigenous status, country of birth and language spoken at home. However, there is limited parental, family and household information available to support understanding of child development.
There has been some linkage undertaken between the AEDC and other datasets (such as the Longitudinal Study of Australian Children, perinatal and births data). However, these studies have tended to focus on the impact of early health on children's development and initial student achievement at school. Other research into early childhood development has generally been at the community level and does not allow for detailed analysis of children's family and household characteristics.
The integrated Tasmania AEDC, NECECC and Census dataset provides a new opportunity to analyse a wide range of socioeconomic characteristics associated with developmental vulnerability for children from different population sub groups. The integrated dataset allows analysis of:
- the relationship between preschool participation and children's development, as moderated by different circumstances such as children in families where all parents are employed
- the extent to which particular personal, household and family characteristics and circumstances affect child development, such as parental engagement in children's schooling, regularity of parent's reading to children, family composition, parental education and household income
- the factors associated with children from lower socioeconomic households having a decreased likelihood of being developmentally vulnerable at the start of school, and conversely, the factors associated with children from higher socioeconomic households having an increased likelihood of being developmentally vulnerable
- population sub groups that may be considered at risk, such as children living with people other than their natural or adopted parents.
Maximising the value of existing administrative data through integration with a range of data (such as the ABS Census), particularly if undertaken at the national level, has the potential to substantially enhance the evidence base for social, economic and educational policy in Australia in a cost effective and efficient way, whilst minimising respondent burden.
SOCIOECONOMIC CONTEXT OF STUDENT ACHIEVEMENT IN TASMANIA
For the first time, data from the ABS Census has been integrated with Tasmanian government school enrolments and National Assessment Program – Literacy and Numeracy (NAPLAN) data to enhance the evidence base about the socioeconomic context of school achievement as well as the longitudinal outcomes of young people post schooling.
To date the key source of information about the pathways and outcomes for students has been measured through longitudinal surveys. The Longitudinal Survey of Australian Youth, for example, measures transitions from schooling into employment or study one to four years post schooling using weighted survey sample data. Other data sources, such as the Survey of Education and Work and State-based school leaver surveys provide transitions information but generally for a limited period of time post-school.
The integrated Tasmanian NAPLAN, government school enrolments and Census dataset provides a new opportunity to analyse longitudinal outcomes of school leavers, and assess how those outcomes are moderated by socioeconomic factors and academic performance. The integrated data allows analysis of:
- the factors that lead to higher performance among children from potentially disadvantaged backgrounds by examining the relationships between socioeconomic and parental characteristics on student performance
- the relationship between school performance and post school outcomes (including income, unpaid work, further study, occupation and housing)
- the factors that lead to better outcomes for school leavers post schooling with fine granularity in terms of field of study, occupation and income, for example, and their outcomes five years after leaving school
- other post school outcomes of students besides engagement with work or study, such as unpaid work caring for a child or a person with disability, or volunteer work
- the pathways and outcomes for Aboriginal and Torres Strait Islander young people, as well as other smaller population sub groups, such as those young people with a disability or from culturally and linguistically diverse backgrounds
- the locational destinations of various student cohorts post schooling (e.g. outcomes for those who have left Tasmania).
MEASURING EDUCATIONAL OUTCOMES OVER THE LIFE-COURSE
These articles provide the results from the Measuring Educational Outcomes over the Life-course project. Information about this project is included on the Public Register of Data Integration Projects on the
National Statistical Service website. Similar analysis is available using Queensland data in
Educational outcomes, experimental estimates, Queensland, 2011 (cat. no. 4261.3).
This project is consistent with the vision and strategies outlined in the Transforming Education and Training Information in Australia (TETIA) initiative. TETIA is a strategy for improving educational outcomes by first building the evidence foundation through facilitating access to data on individuals undertaking education and training, related contextual factors and relevant outcomes; and, second, addressing data gaps in child development and education and training statistics, particularly their cross-sectoral aspects.